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2/ e.g. Why weren't pretrained Unets or transfer learning employed in GANs in late 2018 for GANs? Probably simply because nobody else was doing it- lack of social validation. It certainly wasn't hard to come up with a proof of concept, especially for a fresh MOOC grad like me.
3/ Same thing seems to have happened with NLP and transfer learning- see ULMFiT and the resulting NLP revolution. You can even say the same thing for neural networks themselves. They didn't even teach them when I took my computer vision and AI university classes in 2004-2005.
4/ Since then, time and time again, it has paid off for me, big time, to simply remember to look where others aren't looking, and to prioritize actual observation over trying uncritically assume that smarter people have already covered the territory and are right.
5/ I just find this incredibly interesting- the subject of how exactly progress in science, tech and culture -actually- happens. I think it has a lot more to do with being ok with "oopsies", asking the right questions, and exploration rather than trying to be right and clever.
I took a class on NN in 2004. They were interesting but kind of useless as computers weren't powerful enough yet.
Yeah I get that- it was even before CUDA. But there was already reason to believe at that point that they were powerful and there were already practical demonstrations of this.
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